• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.05a
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• pp.1015-1018
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• 2006

In this paper, new topology optimization technique is proposed. It mainly uses the strain energy distributions induced by the mode shapes associated with natural frequencies of the structure and so we can implicitly consider the dynamic characteristics of the structure in the topology optimization process. The strain energy to be minimized is employed as the objective function and the initial volume of structures is adopted as the constraint function. The resizing algorithm devised from the optimality criteria method is used to update the hole size of the cell existing in each finite element. The cantilever beam problem is adopted to test the proposed techniques. From numerical test, it is found to be that the optimum topology of the cantilever produced by the proposed technique has a hugh increase of natural frequency value and the technique is very effective to maximize the fundamental frequency of the structure.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.21 no.4
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• pp.317-324
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• 2008

Optimum design for general or complex structures are required to the need of many numbers of structural analyses. However, current computational environment with single processor is not capable of generating a high-level efficiency in structural analysis and design process for complex structures. In this paper, a virtual parallel computing system communicated by an internet of personal computers and workstation is constructed. In addition, a routine executing Pro/E, ANSYS and optimization algorithm automatically are adopted in the distributed process technique of sequential approximate optimization for the purpose of enhancing the flexibility of application to general structures. By employing the distributed processing technique during structural analysis using commercial application, total calculation time could be reduced, which will enhance the applicability of the proposed technique to the general complex structures.

• Wind and Structures
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• v.14 no.6
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• pp.559-582
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• 2011

This paper presents an integrated wind-induced dynamic analysis and computer-based design optimization technique for minimizing the structural cost of general tall buildings subject to static and dynamic serviceability design criteria. Once the wind-induced dynamic response of a tall building structure is accurately determined and the optimal serviceability design problem is explicitly formulated, a rigorously derived Optimality Criteria (OC) method is to be developed to achieve the optimal distribution of element stiffness of the structural system satisfying the wind-induced drift and acceleration design constraints. The effectiveness and practicality of the optimal design technique are illustrated by a full-scale 60-story building with complex 3D mode shapes. Both peak resultant acceleration criteria and frequency dependent modal acceleration criteria are considered and their influences on the optimization results are highlighted. Results have shown that the use of various acceleration criteria has different implications in the habitability evaluations and subsequently different optimal design solutions. The computer based optimization technique provides a powerful tool for the lateral drift and occupant comfort design of tall building structures.

• Journal of Electrical Engineering and Technology
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• v.12 no.2
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• pp.911-917
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• 2017

There are generally three folds when developing neural network classifiers. They are as follows: 1) discriminant function; 2) lots of parameters in the design of classifier; and 3) high dimensional training data. Along with this viewpoint, we propose space search optimized polynomial neural network classifier (PNNC) with the aid of data preprocessing technique and simultaneous tuning strategy, which is a balance optimization strategy used in the design of PNNC when running space search optimization. Unlike the conventional probabilistic neural network classifier, the proposed neural network classifier adopts two type of polynomials for developing discriminant functions. The overall optimization of PNNC is realized with the aid of so-called structure optimization and parameter optimization with the use of simultaneous tuning strategy. Space search optimization algorithm is considered as a optimize vehicle to help the implement both structure and parameter optimization in the construction of PNNC. Furthermore, principal component analysis and linear discriminate analysis are selected as the data preprocessing techniques for PNNC. Experimental results show that the proposed neural network classifier obtains better performance in comparison with some other well-known classifiers in terms of accuracy classification rate.

• Smart Structures and Systems
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• v.22 no.4
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• pp.469-479
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• 2018

The present research study utilizes a multi-objective optimization method for Pareto optimization of an eight-degree of freedom full vehicle vibration model, adopting a non-dominated sorting genetic algorithm II (NSGA-II). In this research, a full set of ride comfort as well as ride safety parameters are considered as objective functions. These objective functions are divided in to two groups (ride comfort group and ride safety group) where the ones in one group are in conflict with those in the other. Also, in this research, a special optimizing technique and combinational method consisting of weighted sum method and Pareto optimization are applied to transform Pareto double-objective optimization to Pareto full-objective optimization which can simultaneously minimize all objectives. Using this technique, the full set of ride parameters of three dimensional vehicle model are minimizing simultaneously. In derived Pareto front, unique trade-off design points can selected which are non-dominated solutions of optimizing the weighted sum comfort parameters versus weighted sum safety parameters. The comparison of the obtained results with those reported in the literature, demonstrates the distinction and comprehensiveness of the results arrived in the present study.

• Structural Engineering and Mechanics
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• v.47 no.4
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• pp.513-530
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• 2013

In this paper, an improved version of particle swarm optimization based optimum design algorithm (IPSO) is presented for the steel grillage systems. The optimum design problem is formulated considering the provisions of American Institute of Steel Construction concerning Load and Resistance Factor Design. The optimum design algorithm selects the appropriate W-sections for the beams of the grillage system such that the design constraints are satisfied and the grillage weight is the minimum. When an improved version of the technique is extended to be implemented, the related results and convergence performance prove to be better than the simple particle swarm optimization algorithm and some other metaheuristic optimization techniques. The efficiency of different inertia weight parameters of the proposed algorithm is also numerically investigated considering a number of numerical grillage system examples.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.8
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• pp.768-776
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• 2011

This paper considers a data fitting problem for rational function models using the LM (Levenberg-Marquardt) optimization method. Rational function models have various merits on representing a wide range of shapes and modeling complicated structures by polynomials of low degrees in both the numerator and denominator. However, rational functions are nonlinear in the parameter vector, thereby requiring nonlinear optimization methods to solve the fitting problem. In this paper, we propose a data fitting method for rational function models based on the LM algorithm which is renowned as an effective nonlinear optimization technique. Simulations show that the fitting results are robust against the measurement noises and uncertainties. The effectiveness of the proposed method is further demonstrated by the real application to a 3D depth camera calibration problem.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2001.04a
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• pp.895-898
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• 2001

This paper presents an optimization cutting speed(OCS) program developed to improve the machining precision and tool life in high speed machining using ball end milling. This program optimized the cutting speed that is changing at any time in free surface machining of an automobile part like a connecting load die. The technique of optimization cutting speed makes the CAD/CAM-generated NC code go through a reverse post process, conducts cutting simulation, and obtain the effective tool diameter of the ball end milling. Then it changes the spindle revolution to within the range of critical cutting speed fit for the material of the workpieces depending upon the effective tool diameter. In this study, the machining precision and tool life were compared for the two connecting load dies processed using the general cutting method and the proposed optimization cutting speed technique, respectively.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.13 no.6
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• pp.107-113
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• 2004

This paper presents the pillar section optimization technique considering the reliability of the vehicle body structure consisted of complicated thin-walled panels. The response surface method is utilized to obtain the response surface models that describe the approximate performance functions representing the system characteristics on the section properties of the pillar and on the mass and the natural frequencies of the vehicle B.I.W. The reliability-based design optimization on the pillar sections Is performed and compared with the conventional deterministic optimization. The FORM is applied for the reliability analysis of the vehicle body structure. The developed optimization system is applied to the pillar section design considering the fundamental natural frequencies of passenger car body structure. By applying the proposed RBDO technique, it can be possible to optimize the pillar sections considering the reliability that engineers require.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.298-298
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• 2000

This paper presents the optimization technique to analyze the effect of the design parameters of rapid prototyping system for human brain model fabrication. The optimization method considers the functional relationships among the design parameters such as thickness gap, shrink rate, and laser speed that govern the operation of fabrication system. This paper applies a discrete optimization technique as the optimization method to determine the dominant parameter values. Additional study includes manner of complement surface image of ellipse which approximates the brain model using the adaptive slicing and the offset contour. According to the parameters tuning and interaction of effect, more suitable parameter values can be obtained by enhanced 3D brain model fabrication.